{"id":1033,"date":"2008-09-06T05:51:42","date_gmt":"2008-09-06T09:51:42","guid":{"rendered":"http:\/\/mseas.net16.net\/?p=1033"},"modified":"2021-08-16T20:29:12","modified_gmt":"2021-08-17T00:29:12","slug":"path-planning-of-autonomous-underwater-vehicles-for-adaptive-sampling-using-mixed-integer-linear-programming","status":"publish","type":"post","link":"https:\/\/mseas.mit.edu\/?p=1033","title":{"rendered":"Path Planning of Autonomous Underwater Vehicles for Adaptive Sampling Using Mixed Integer Linear Programming"},"content":{"rendered":"The goal of adaptive sampling in the ocean is to predict\r\nthe types and locations of additional ocean measurements that\r\nwould be most useful to collect. Quantitatively, what is most useful\r\nis defined by an objective function and the goal is then to optimize\r\nthis objective under the constraints of the available observing network.\r\nExamples of objectives are better oceanic understanding, to\r\nimprove forecast quality, or to sample regions of high interest. This\r\nwork provides a new path-planning scheme for the adaptive sampling\r\nproblem. We define the path-planning problem in terms of\r\nan optimization framework and propose a method based on mixed\r\ninteger linear programming (MILP). The mathematical goal is to\r\nfind the vehicle path that maximizes the line integral of the uncertainty\r\nof field estimates along this path. Sampling this path can improve\r\nthe accuracy of the field estimates the most. While achieving\r\nthis objective, several constraints must be satisfied and are implemented.\r\nThey relate to vehicle motion, intervehicle coordination,\r\ncommunication, collision avoidance, etc. The MILP formulation is\r\nquite powerful to handle different problem constraints and flexible\r\nenough to allow easy extensions of the problem. The formulation\r\ncovers single- and multiple-vehicle cases as well as singleand\r\nmultiple-day formulations. The need for a multiple-day formulation\r\narises when the ocean sampling mission is optimized for\r\nseveral days ahead. We first introduce the details of the formulation,\r\nthen elaborate on the objective function and constraints, and\r\nfinally, present a varied set of examples to illustrate the applicability\r\nof the proposed method.","protected":false},"excerpt":{"rendered":"<p>The goal of adaptive sampling in the ocean is to predict the types and locations of additional ocean measurements that would be most useful to collect. Quantitatively, what is most useful is defined by an objective function and the goal is then to optimize this objective under the constraints of the available observing network. Examples [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[182,183,34,35,5,185,194,62,63],"tags":[],"class_list":["post-1033","post","type-post","status-publish","format-standard","hentry","category-learning-and-data-assimilation","category-science-of-autonomy","category-data-assimilation","category-optimal-path-planning","category-publications","category-adaptive-sampling","category-papers-in-refereed-journals-adaptive-sampling","category-papers-in-refereed-journals-data-assimilation","category-papers-in-refereed-journals-optimal-path-planning"],"_links":{"self":[{"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/posts\/1033","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1033"}],"version-history":[{"count":2,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/posts\/1033\/revisions"}],"predecessor-version":[{"id":1160,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/posts\/1033\/revisions\/1160"}],"wp:attachment":[{"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1033"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1033"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1033"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}